remove errors from sample, add tests

sample/samplers.go

@@ -2,7 +2,6 @@ package sample
 
 import (
 	"errors"
-	"log/slog"
 	"math"
 	"math/rand/v2"
 	"slices"
@@ -37,10 +36,7 @@ func (s *Sampler) Sample(logits []float32) (int32, error) {
 		tokens[i].value = logits[i]
 	}
 
-	t, err := s.sample(tokens)
-	if err != nil {
-		return -1, err
-	}
+	t := s.sample(tokens)
 
 	if s.grammar != nil {
 		// optimization: first check if the max logit is accepted by the grammar
@@ -60,10 +56,7 @@ func (s *Sampler) Sample(logits []float32) (int32, error) {
 			tokens[i].value = logits[i]
 		}
 		s.grammar.Apply(tokens)
-		t, err = s.sample(tokens)
-		if err != nil {
-			return -1, err
-		}
+		t = s.sample(tokens)
 		s.grammar.Accept(t.id)
 	}
 
@@ -84,9 +77,9 @@ func greedy(tokens []token) token {
 
 // sample returns the highest probability token from the tokens
 // given sampler parameters. It also has side effects of modifying the tokens
-func (s *Sampler) sample(tokens []token) (token, error) {
+func (s *Sampler) sample(tokens []token) token {
 	if s.temperature == 0 {
-		return greedy(tokens), nil
+		return greedy(tokens)
 	}
 
 	// topK also sorts the tokens in descending order of logits
@@ -99,12 +92,6 @@ func (s *Sampler) sample(tokens []token) (token, error) {
 	tokens = topP(tokens, s.topP)
 	tokens = minP(tokens, s.minP)
 
-	// fallback to greedy sampling if no tokens are left
-	if len(tokens) == 0 {
-		slog.Warn("sample: no tokens left after applying transforms, falling back to greedy sampling")
-		return greedy(tokens), nil
-	}
-
 	var r float32
 	if s.rng != nil {
 		r = s.rng.Float32()
@@ -127,7 +114,7 @@ func (s *Sampler) sample(tokens []token) (token, error) {
 		return 1
 	})
 
-	return tokens[idx], nil
+	return tokens[idx]
 }
 
 // TODO(parthsareen): update sampler interface to use json unmarshal https://github.com/ollama/ollama/issues/9278

sample/samplers_test.go

@@ -29,6 +29,20 @@ func TestWeighted(t *testing.T) {
 	if want != got {
 		t.Errorf("index mismatch: want %d, got %d", want, got)
 	}
+
+	// Test greedy fallback when sample() returns error
+	logits = []float32{1.0, 0.999, 0.5, 0.1}
+	// Use extremely small topP to filter out all tokens, forcing error and greedy fallback
+	sampler = NewSampler(1.0, 0, 1e-10, 0, 0, nil)
+	got, err = sampler.Sample(logits)
+	if err != nil {
+		t.Error(err)
+		return
+	}
+	want = int32(0) // Should fall back to greedy and pick highest logit
+	if want != got {
+		t.Errorf("greedy fallback: want %d, got %d", want, got)
+	}
 }
 
 func BenchmarkSample(b *testing.B) {

sample/transforms_test.go

@@ -171,7 +171,7 @@ func TestTopP(t *testing.T) {
 	// Test with very high p value
 	got := topP(tokens, 1.0)
 
-	// Should keep almost all tokens since p is very high
+	// Should keep all tokens since p is 1
 	if len(got) != len(input) {
 		t.Errorf("topP(1.0): should keep all tokens, got %d, want %d", len(got), len(input))
 	}
@@ -179,17 +179,17 @@ func TestTopP(t *testing.T) {
 	// Test with normal p value
 	got = topP(tokens, 0.95)
 
-	// Should keep tokens until cumulative probability > 0.95
 	if len(got) > 3 {
 		t.Errorf("topP(0.95): kept too many tokens: got %d", len(tokens))
 		t.Logf("got: %v", got)
 	}
 
 	// Test edge case - ensure at least one token remains
-	input = []float32{-1e6, -1e6, -1e6} // One dominant token
+	input = []float32{-1e6, -1e6, -1e7}
 	tokens = toTokens(input)
+	tokens = topK(tokens, 20)
 	softmax(tokens)
-	got = topP(tokens, 0.0) // Very small p
+	got = topP(tokens, 0.0)
 	if len(got) < 1 {
 		t.Error("topP should keep at least one token")
 	}
@@ -202,10 +202,19 @@ func TestTopP(t *testing.T) {
 		t.Errorf("topP(0.0): should keep only one token, got %d", len(got))
 		t.Logf("got: %v", got)
 	}
+
+	tokens = toTokens(input)
+	tokens = topK(tokens, 20)
+	softmax(tokens)
+	got = topP(tokens, 1e-10)
+	if len(got) == 0 {
+		t.Errorf("topP(1e-10): should keep at least one token, got %d", len(got))
+		t.Logf("got: %v", got)
+	}
 }
 
 func TestMinP(t *testing.T) {
-	input := []float32{-3, -2, -1, 0, 1, 2, 4, 3}
+	input := []float32{-2, 0, -1, -3, 2, 1, 4, 3}
 	tokens := toTokens(input)
 
 	// First apply temperature and softmax
@@ -242,6 +251,18 @@ func TestMinP(t *testing.T) {
 		t.Logf("got: %v", tokens)
 	}
 
+	// Test with single token
+	tokens = toTokens(input[:1])
+	tokens = topK(tokens, 20)
+	softmax(tokens)
+	tokens = minP(tokens, 0.1)
+
+	// Should keep only the highest probability token
+	if len(tokens) != 1 {
+		t.Errorf("minP(0.1): should return single token, got %d", len(tokens))
+		t.Logf("got: %v", tokens)
+	}
+
 	input = []float32{1e-10, 1e-10, 1e-10}
 	tokens = toTokens(input)
 	softmax(tokens)